Smartphone specs are on the verge of transferring backward within the close to future, not resulting from an absence of innovation, however to the dramatic rise in the price of a key element: reminiscence. DRAM and NAND prices are rising sharply and are anticipated to remain excessive via not less than the primary half of 2026.

Suppliers are elevating costs resulting from a surge in demand for AI servers, knowledge facilities, and enterprise {hardware} options. The pressure first showed up in PC RAM prices; it’s now spilling over into units like smartphones, tablets, and smartwatches.

All the favored manufacturers you understand will reply by doing certainly one of three: elevating costs, slicing margins, or quietly downgrading the RAM in upcoming fashions. Whereas slicing margins is the least probably situation, producers are prone to improve costs or lower system reminiscence capability, particularly for units that account for a big share of their gross sales.

For smartphones, this implies you won’t discover 16GB of RAM anymore, even on high fashions (a couple of exceptions might exist), fewer 12GB RAM fashions (by over 40%), and 8GB fashions lowered by over 50% (by way of a submit on the Korean blog Naver).

Lesser RAM may very well be a bottleneck for on-device AI options

To mitigate worth impacts, Xiaomi has already been contemplating trimming RAM on particular 2026 smartphone fashions (by way of GizChina). Together with it, different Chinese language smartphone giants like OnePlus, Vivo, Oppo, and world manufacturers like Samsung and Google, must also face the warmth, resulting in a uncommon second in smartphone historical past the place specs might stagnate and even regress, at the same time as software program calls for proceed to rise.

In contrast to cloud-based AI, on-device fashions require substantial reminiscence, which is why you see flagship Android units, and even the midrange ones, that includes greater than 8GB of RAM. If smartphone makers scale back the system’s bodily reminiscence, it might depart much less room for the AI mannequin and apps to coexist, resulting in aggressive RAM administration, app reloads, or sluggish AI options.

Furthermore, the rising variety of on-device AI options and the looming risk of provide chain constraints on reminiscence may push smartphone specs again by not less than a couple of years (with software program progressing to 2026). Even when the producers determine to retain an identical reminiscence, there’s a great probability that they’ll move on the extra price to prospects.

To place it merely, your subsequent Android smartphone may both be costlier or noticeably much less responsive. Whereas firms usually promote flagships at greater margins, leaving extra room for price changes, the influence may very well be worse on midrange units, which are sometimes offered at decrease margins: patrons may find yourself paying extra for decrease specs.

An issue centered on the midrange section

Strictly talking, in america market, the reminiscence conundrum issues most within the $400 to $800 section, the place Android smartphones prioritize efficiency per greenback and longevity above all else.

And sure, Apple’s iPhones may additionally get a style of it, as the corporate leans on tighter software program optimization and chipset effectivity than onboard reminiscence. However that doesn’t imply that the corporate is fully immune both. If the situation doesn’t enhance and the worth of high-quality RAM goes up, Apple patrons may need to pay a premium for the extent of efficiency they’re used to.

Laptop computer makers may additionally focus extra on lowering shipments with over 16GB of RAM (by over 60%). As an alternative, the manufacturers may focus extra on 8GB RAM variants, primarily as a result of excessive quantity of onboard fashions, however a worth hike may accompany them.

If reminiscence costs stay excessive, producers must make long-term selections concerning the form of smartphones, tablets, and different client units that they wish to ship. We may see sharper segmentation, with premium fashions retaining greater RAM, tighter software program optimization, and fewer AI-based options on lower-memory or budget-centric units.

Reminiscence as a bottleneck may additionally compel Google to rethink how the Gemini Nano mannequin is deployed on units and the quantity of system sources it consumes. The trade as an entire may undertake hybrid AI approaches, by which some options are dealt with on the system, and others are outsourced to the cloud. Will producers reserve sure AI-based options for the highest trims of their fashions?